Scenario analysis of smart, sustainable supply chain on the basis of a fuzzy cognitive map

Abstract

Purpose

This paper aims to present a smart, sustainable supply chain practices structure on the basis of the relational view.

Design/methodology/approach

A method based on fuzzy cognitive map was applied to construct a relational map to introduce and implement such relational methods. Considering this relational map as a guideline, observations into particular methods and ways of applying relational methods to attain sustainable development goals across organizations has been introduced.

Findings

Primary outcomes provided a series of relational methods for the purpose of giving advice to those organizations and their suppliers for smart, sustainable supply chain. Reliance between relational methods were examined and assessed under seven meaningful groups: economic internet of things (IoT), green internet of things, social internet of things, economic supply chain, green supply chain, social supply chain and other variables.

Practical implications

This study guides managers toward an improved perception of the connection among IoT instances and sustainable supply to modeling smart, sustainable supply chain. Managers can determine the practices that need more focus along with the practices that are less relevant. Thus, this will help managers in the decision-making process and to organize their decisions by planning and calculating the relative importance and influence of smart, sustainable practices on each other and on the company’s smart, sustainable program.

Originality/value

To the best of the authors’ knowledge, this is the first approach that promptly examines and determines the interdependencies between relational methods and constructs a relational map for the purpose to introduce and analyze smart, sustainable supply chain.

Citation

Shokouhyar, S., Pahlevani, N. and Mir Mohammad Sadeghi, F. (2019), "Scenario analysis of smart, sustainable supply chain on the basis of a fuzzy cognitive map", Management Research Review, Vol. 43 No. 4, pp. 463-496. https://doi.org/10.1108/MRR-01-2019-0002